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Seasonality in fruit availability affects frugivorous primate biomass and species richness

2011· article· en· W1976949835 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEcography · 2011
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsMcGill University
FundersOphthalmic Research Institute of Australia
KeywordsFrugivoreSpecies richnessSeasonalityEcologyBiogeographyMainlandBiomass (ecology)BiologyPrimateAbundance (ecology)Insular biogeographyHabitat

Abstract

fetched live from OpenAlex

We examine the effect of total annual food abundance and seasonal availability on the biomass and species richness for frugivorous primates on three continents (n=16 sites) by data on fruit fall. We reveal that the best‐fit models for predicting primate biomass include total annual fruit fall (positive), seasonality (negative) and biogeography (Old World>New World and mainland>island) and that these factors explain 56–67% of the variation. For the number of species, the best‐fit models include seasonality (negative) and biogeography (Old World>New World and mainland>island) but not total annual fruit fall. Annual temperature has additional effects on primate biomass when the effects of fruits and biogeography are controlled, but there is no such effect on species richness. The present results indicate that, measured on local scales, primate biomass and number of species is affected by the seasonal variation in food availability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.297
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it